2018
DOI: 10.1590/01047760201824012466
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HEIGHT-DIAMETER MODELS FOR Eucalyptus sp. PLANTATIONS IN BRAZIL

Abstract: HEIGHT-DIAMETER MODELS FOR Eucalyptus sp. PLANTATIONS IN BRAZILFERRAZ FILHO, A. C.; MOLA-YUDEGO, B.; RIBEIRO, A.; SCOLFORO, J. R. S.; LOOS, R. A.; SCOLFORO, H. F. Height-diameter models for Eucalyptus sp. plantations in Brazil. CERNE, v. 24, n. 1, p. 9-17, 2018. HIGHLIGHTSHeight-diameter models are provided for eucalyptus plantations in Brazil.A wide variety of stand conditions (age and tree densities) were covered in the database.Mixed modeling was used due to the hierarchical structure of the data (trees in … Show more

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Cited by 23 publications
(16 citation statements)
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References 44 publications
(36 reference statements)
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“…However, in the present study, it was observed that linear regression may also overcome the ANNs, contrary to other studies [21,38,39]. In addition, regression models are easier to implement and can provide logical estimates under extrapolation [1,40]. Thus, the comparison between the two methods is valid to investigate which is more appropriate for data modeling.…”
Section: Discussioncontrasting
confidence: 57%
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“…However, in the present study, it was observed that linear regression may also overcome the ANNs, contrary to other studies [21,38,39]. In addition, regression models are easier to implement and can provide logical estimates under extrapolation [1,40]. Thus, the comparison between the two methods is valid to investigate which is more appropriate for data modeling.…”
Section: Discussioncontrasting
confidence: 57%
“…Eucalyptus plantations are located all over the world [1]. In Brazil, most tree species used to supply the forest industry are of the genus Eucalyptus; they have favorable characteristics for the industry and can adapt to different edaphic and climatic conditions [2,3].…”
Section: Introductionmentioning
confidence: 99%
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“…Linearization of biomass models has been used in many studies (Repola, 2008;Litton & Boone, 2008;Mugasha et al, 2013;Chave et al, 2014), mainly due to its simplicity (Ferraz Filho et al, 2018). Alternatively, other approaches can be used to increase the accuracy of growth predictions of forest stands such as Artificial Neural Networks (Binoti et al, 2013;Reis et al, 2016;Ferraz Filho et al, 2018), support vector machines (Cordeiro et al, 2015;Cosenza et al, 2015) and Quantile Regression (Araújo et al, 2016). However, these methods are computationally intensive and should be used with caution due to potential restrictions on extrapolations (Ferraz Filho et al, 2018).…”
Section: Model Validationmentioning
confidence: 99%
“…The mixedeffects models were then introduced in forest mensuration as a new approach to model the longitudinal profile of stems (Cao & Wang 2011, Gomez-García et al 2013. In addition to the fixed effects that are common to all individuals, they include parameters with random effects that are unique to individuals or groups within the data set (Calama & Montero 2006, Cao & Wang 2011, Gomez-García et al 2013, Ruslandi et al 2017, Ferraz-Filho et al 2018.…”
Section: Introductionmentioning
confidence: 99%